Methods Development

The following are new exposure and response measures as well as statistical methods developed and validated by CHEAR Lab Hubs and Data Center to investigate the uses of a range of accessible biological samples for children’s health studies.

Crotonaldehyde (2-butenal), a toxicant and carcinogen, is present in tobacco smoke (5-20 µg per cigarette). A major pathway of crotonaldehyde metabolism is conjugation with glutathione resulting ultimately in urinary excretion of 3-hydroxy-1-methylpropylmercapturic acid (HMPMA-1), which has been analyzed by LC-MS/MS as a biomarker of crotonaldehyde exposure. We examined the hypothesis that the corresponding isomeric mercapturic acids from the smoke constituents 2-methylacrolein (HMPMA-2) and methylvinyl ketone (HMPMA-3) could coelute with HMPMA-1 under the conditions reported for its analysis. Therefore, a new HPLC system was developed which separates HMPMA-1, -2, and -3. This allowed us to determine, for the first time, levels of these individual mercapturic acids in the urine of smokers and non-smokers.

This work was presented at the 67th American Society for Mass Spectrometry Conference on Mass Spectrometry and Allied Topics, June 2–6, 2019, in Atlanta, Georgia.

A rapid method for the analysis of perfluorinated alkyl substances in serum by hybrid solid-phase extraction

A method for the analysis of 13 perfluorinated alkyl substances (PFASs) in human serum was developed based on hybrid solid-phase extraction (hybrid-SPE) and ultrahigh-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS). Serum PFASs were extracted using hybrid-SPE-phospholipid cartridge after precipitating proteins and other endogenous biological interferences with 1% ammonium formate in methanol. The average intra-day accuracy (measured as percent recoveries from fortified samples) and precision of the method (measured as relative standard deviation [RSD, %] between analyses) were 88.7–117% and 1.0–13.4%, respectively. The average inter-day precision was 2.8–6.9 %. The method was sensitive, with limits of quantification (LOQs) in the range of 0.05 to 0.09 ng mL1 for all 13 PFASs. The applicability of this method was tested by analysing serum-certified standard reference material and proficiency test samples. In an hour, 100 samples can be processed by hybrid-SPE, and the instrumental run time is 5 min per sample. The developed method is rapid, inexpensive, accurate, precise, and extremely sensitive for the analysis of PFASs in human serum.

Method for the determination of iodide in dried blood spots from newborns by high performance liquid chromatography tandem mass spectrometry

Dried blood spots (DBS), collected for newborn screening programs in the United States, have been used to screen for congenital metabolic diseases in newborns for over 50 years. DBS provide an easy and inexpensive way to collect and store peripheral blood specimens and present an excellent resource for studies on the assessment of chemical exposures in newborns. In this study, a selective and sensitive method was developed for the analysis of iodide in DBS by high performance liquid chromatography electrospray tandem mass spectrometry. Accuracy, inter- and intraday precision, matrix effects, and detection limits of the method were determined. Further validation of the method was accomplished by concurrent analysis of whole blood and fortified blood spotted on a Whatman 903 filter card. A significant positive correlation was found between measured concentrations of iodide in venous whole blood and the same blood spotted as DBS. The method limit of detection was 0.15 ng/mL iodide. The method was further validated by the analysis of a whole blood sample certified for iodide levels (proficiency testing sample) by spotting on a filter card. Twenty DBS samples collected from newborns in New York State were analyzed to demonstrate the applicability of the method. The measured concentrations of iodide in whole blood of newborns from New York State ranged between <LOD and 16.4 ng/mL. The developed method is applicable for the analysis of DBS collected for epidemiological studies that investigate the importance of iodide on the health of newborns.

Follicular fluid (FF), which is the fluid that envelops the developing oocyte (egg cell) in the ovary, can be analyzed to assess trace element content as well as to determine potential exposure to toxic elements in women seeking in vitro fertilization (IVF) treatment. Such measurements may be useful in establishing associations with potential adverse effects on oocyte viability and subsequent pregnancy outcomes. The principal goal of this study was to leverage the next generation of inorganic mass spectrometry based on ICP-MS/MS to address the numerous analytical challenges of (ultra-)trace element analysis of human FF specimens. Ultra-trace element measurements are defined by the Clinical Laboratory Standards Institute as fluid concentrations below 10 µg L-1 or tissue mass fractions below 1 µg g-1. Stringent pre-analytical procedures were developed to minimize exogenous contamination during FF specimen collection and storage in a prospective study of 56 women seeking IVF treatment. ICP-MS/MS instrumental parameters were carefully optimized, and the method validated for 11 biologically important elements that included 4 at trace levels (Cu, Se, Sr, and Zn) and 7 at ultra-trace levels (As, Cd, Co, Mo, Mn, Hg, and Pb). Method limits of detection (LODs) varied from 5.6 ng L-1 for Cd to 0.11 µg L-1 for Mo. A total of 197 human FF specimens were analyzed using the proposed ICP-MS/MS method with 84% of specimens detectable for Pb and 100% detectable for Co, Cu, Mn, Mo, Sr, and Zn. The method based on ICP-MS/MS was compared to a previous method developed for FF using SF-ICP-MS.

A single semi-targeted analytical method for quantification of multiple classes of environmental toxicants in human urine using liquid chromatography-high resolution mass spectrometry

To begin to assess the complex exposome of humans, an analytical approach is needed that can capture dozens, or even hundreds, of biomarkers simultaneously. The greatest challenge in such a method is that most of the environmental chemicals of interest are present at trace levels (ng/ml to ag/mL range); their detection can be obscured by the presence of endogenous chemicals at high concentrations. We have developed a method that is capable of quantifying 40 environmental chemicals and over 35 dietary phenolic chemicals in a single 1-mL urine sample. The chemical classes represented include phthalates, environmental phenols including BPA and its analogues, organophosphate and pyrethroid insecticides, phenoxy acid herbicides, parabens, polycyclic aromatic hydrocarbons, phytoestrogens and dietary phenols including vanillic acid, hydroxybenzoic acids, apigenin, caffeic acid, and coumaric acids which collectively represent endocrine modulating chemicals, carcinogens, and neurotoxicants. Our method employs a novel differential isotopic label coding scheme for quantification. Briefly, a 1-mL urine sample is subjected to enzymatic deconjugation to liberate glucuronide- and sulfate-bound analytes. The hydrolysate is extracted using StrataX polymeric solid phase extraction. The extract is derivatized with 12C-dansyl chloride then is combined with a reference sample which was extracted and derivatized concurrently with 13C-dansylchloride. The extracts are analyzed using liquid chromatography-Fourier Transform mass spectrometry (FTMS) which can capture high resolution full-scan data. The ratio of 12C-dansyl derivatives/13C-dansyl derivatives in the reference sample is used for quantification. The limits of detection are in the low- to mid-pg/mL range. We are currently in the final stages of validation. Because of the universal collection of high resolution FTMS data, the chemicals targeted for quantification are limited only by their presence in the reference standard. This technique also allows the collection of “unknown” analyte signals that can be further investigated and identified. With the subsequent addition of the identified chemicals to the reference standard, quantification of these newly identified chemicals can be achieved. This method is restricted to those chemicals with a functional group (e.g., -OH, -COOH, NH4) that is derivatizable by dansyl chloride, which includes most environmental chemical metabolites that are excreted in urine.

This work was presented at South Eastern Regional Meeting of the American Chemical Society, Augusta GA, October 31,2018 to to November 3, 2018.

Interstitial fluid (ISF) surrounds the cells and tissues of the body. Since ISF has molecular components similar to plasma, as well as compounds produced locally in tissues, it may be a valuable source of biomarkers for diagnostics and monitoring. However, there has not been a comprehensive study to determine the metabolite composition of ISF and to compare it to plasma. In this study, the metabolome of suction blister fluid (SBF), which largely consists of ISF, collected from 10 human volunteers was analyzed using untargeted high-resolution metabolomics (HRM). A wide range of metabolites were detected in SBF, including amino acids, lipids, nucleotides, and compounds of exogenous origin. Various systemic and skin-derived metabolite biomarkers were elevated or found uniquely in SBF, and many other metabolites of clinical and physiological significance were well correlated between SBF and plasma. In sum, using untargeted HRM profiling, this study shows that SBF can be a valuable source of information about metabolites relevant to human health.

Analysis of endogenous and exogenous metabolites using untargeted high-resolution LC-MS

Individuals have many types of exposures (e.g., medications, illicit drugs, environmentally relevant chemicals, and constituents in foods) that cause perturbations in the endogenous metabolome. Untargeted analysis provides the opportunity to simultaneously detect signals derived from both the endogenous metabolome (those metabolites that map to biochemical pathways) and the exogenous (derived from exposures) metabolome. We have developed and applied high-resolution liquid chromatography-mass spectrometry (Q-Exactive HFxTM; and Synapt G2Si) method to analyze endogenous and exogenous metabolites in urine, serum, plasma stool, hair and sweat collected from human subjects. The system resolves 10,000 to 40,000 features, depending on the biospecimen. We use a variety of modelling approaches (supervised and unsupervised multivariate statistics, linear and logistic regression, and structural equation modeling) to reveal patterns and data trends that show the correlation of signals with phenotypic responses. We match signals to our in-physical standards library (Retention Time, MS, MS/MS library) and also use big data analytics for matching signals to public databases. Our in-house physical standards library was constructed with over 1,200 endogenous compounds, environmentally relevant chemicals, and over-the-counter and prescribed medications and illicit drugs. To ensure rigor in communication of results, and to improve the ability to compare and harmonize results data between laboratories, we developed a system to label the confidence for each identification or annotation. Analysis of biospecimens for the CHEAR and ECHO program results in the assignment of endogenous metabolites, as well as the parent compound and metabolites derived from exogenous exposures. Endogenous metabolites include carboxylic acids, amino acids, biogenic amines, polyamines, bases, nucleosides and nucleotides, coenzymes and vitamins, mono- and disaccharides, fatty acids, lipids, steroids and hormones. Exogenous compounds include metabolites of alkyl phosphate pesticides, environmental phenols, polyaromatic hydrocarbons, parabens, PFASs, phthalates, tobacco use, volatile organic compounds, over the counter medications (e.g., acetaminophen), illicit drugs (e.g., opioids) and foods (e.g., phenolics).

This approach provides a robust platform for analysis of a wide range of analytes in a variety of biospecimens, with the ability to interrogate the collected data using approaches for understanding both exposure to exogenous chemicals and effects on endogenous metabolism.

This work was presented at the 14th Annual Conference of the Metabolomics Society, Seattle, WA, June 24-28, 2017.

Metabolomics applications of differential mobility spectrometry (DMS)-mass spectrometry (MS) have largely concentrated on targeted assays and the removal of isobaric or chemical interferences from the signals of a small number of analytes. M-CHEAR has systematically investigated the application range of a DMS-MS method for metabolomics using more than 800 authentic metabolite standards as the test set. The coverage achieved with the DMS-MS platform was comparable to that achieved with chromatographic methods. High orthogonality was observed between hydrophilic interaction liquid chromatography and the 2-propanol-mediated DMS separation, and previously observed similarities were confirmed for the DMS platform and reversed-phase liquid chromatography. We describe the chemical selectivity observed for selected subsets of the metabolite test set, such as lipids, amino acids, nucleotides, and organic acids. Furthermore, we rationalize the behavior and separation of isomeric aromatic acids, bile acids, and other metabolites.

Liquid chromatography-mass spectrometry-based metabolomics studies require highly selective and efficient chromatographic techniques. Typically employed reversed-phase (RP) methods fail to target polar metabolites, but the introduction of hydrophilic interaction liquid chromatography (HILIC) is slow due to perceived issues of reproducibility and ruggedness and a limited understanding of the complex retention mechanisms. In this study, we present a comparison of the chromatographic performance of a traditional RP-C18 column with zwitterionic, amide-, alkyl diol-, and aminoalkyl-based HILIC and mixed-mode columns. Our metabolite library represents one of the largest analyte sets available and consists of 764 authentic metabolite standards, including amino acids, nucleotides, sugars, and other metabolites, representing all major biological pathways and commonly observed exogenous metabolites (drugs). The coverage, retention patterns, and selectivity of the individual methods are highly diverse even between conceptually related HILIC methods. Furthermore, we show that HILIC sorbents having highly orthogonal selectivity and specificity enhance the coverage of major metabolite groups in (semi-) targeted applications compared to RP. Finally, we discuss issues encountered in the analysis of biological samples based on the results obtained with human plasma extracts. Our results demonstrate that fast and highly reproducible separations on zwitterionic columns are feasible, but knowledge of analyte properties is essential to avoid chromatographic bias and exclusion of key analytes in metabolomics studies. Graphical Abstract The chromatographic parameters of 764 authentic metabolite standards provide the basis for a comparison of coverage, selectivity and orthogonality of 7 reversed-phase (RP), mixed-mode (MM) and hydrophilic interaction liquid chromatography (HILIC) methods.

Simultaneous analysis of seven biomarkers of oxidative damage to lipids, proteins, and DNA in urine

The determination of oxidative stress biomarkers (OSBs) is useful for the assessment of health status and progress of diseases in humans. Whereas previous methods for the determination of OSBs in urine were focused on a single marker, in this study, we present a method for the simultaneous determination of biomarkers of oxidative damage to lipids, proteins, and DNA. 2,4-Dinitrophenyl-hydrazine (DNPH) derivatization followed by solid phase extraction (SPE) and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) allowed the determination of 8-hydroxy-2′-deoxyguanosine (8-OHdG), o-o′-dityrosine (diY), malondialdehyde (MDA), and four F2-isoprostane isomers: 8-iso-prostaglandinF2α (8-PGF2α), 11β-prostaglandinF2α (11-PGF2α), 15(R)-prostaglandinF2α (15-PGF2α), and 8-iso,15(R)-prostaglandinF2α (8,15-PGF2α) in urine. Derivatization with DNPH and SPE was optimized to yield greater sensitivity and selectivity for the analysis of target chemicals. The limits of detection of target analytes in urine were below 30 pg mL−1. The assay intra- and interday variability was below 16% of the relative standard deviation, and the recoveries of target chemicals spiked into synthetic urine were near 100%. The method was applied to the analysis of 21 real urine samples, and the analytes were found at a detection frequency of 85% for 8-PGF2α and 15-PGF2α, 71% for 11-PGF2α, 81% for 8,15-PGF2α, and 100% for diY, 8-OHdG, and MDA. This method offers simultaneous determination of multiple OSBs of different molecular origin in urine samples selectively with high accuracy and precision.

Research in children’s environmental health demonstrates that consequences of adverse or toxic environmental exposures during critical periods in development can manifest as disease or dysfunction across the human life span. Children are particularly vulnerable to adverse health risks from factors including exposures to environmental contaminants, poor nutrition, and stress because their major organ systems are developing from conception through adolescence. These factors are multi-dimensional and complex—not simple, single exposures related to a single health outcome. As such, the Data Center statistics group is conducting ongoing biostatistical methods development in multiple CHEAR-related projects. A useful strategy for evaluating the mixture effect of complex environmental exposures is generalized weighted quantile sum (WQS) regression, resulting in the construction of an empirically weighted index of exposure quantiles, and is implemented through the gWQS R package. We have enhanced its capability by including options for multinomial data (generalized logit regression) and count data (Poisson regression). We have demonstrated its use in the analysis of mixtures of prenatal nutrients and neurodevelopment. We have also extended the method for analysis of hundreds and even thousands of components by using a random subset ensemble step; simulation studies demonstrate high sensitivity and specificity. We have used this version of WQS regression in the analysis of metabolomics data. But the choice of methods for evaluating mixtures depends on the research question. We have written a joint paper using multiple mixture strategies on metabolomics data – shrinkage methods (lasso), random forest, network analyses, WQS regression, and latent class analyses. We are also developing and evaluating strategies for using CHEAR data in matched case-control studies where cases are selected from national registries of identified pediatric diseases (e.g., autism, liver disease) with samples evaluated in CHEAR. Finally, the CHEAR data center is developing the use of multivariable control charts for evaluating the measurement consistency in CHEAR pool samples across studies and across labs. To ensure rigor and reproducibility, we have made the workflows we have developed publically available on GitHub.

Teeth develop in layers, similar to growth rings in trees, and capture exposure information in a temporally incremental manner. We have developed methods to undertake a hybrid targeted-untargeted metallomics scan with a temporal resolution of 1 to 2 weeks. This assay allows us to undertake a highly time resolved analysis of metal uptake from the second trimester to the first year of life. In a single scan, this analysis can measure over 15 elements, including essential nutrients and toxic metals. In combination with a novel statistical method, the reverse distributed lag model (DLM) developed by colleagues at the CHEAR Data Center, we applied this new assay to study twins discordant for autism spectrum disorder (ASD). We found that even in MZ twins, there are differences in prenatal uptake of metals that ultimately increase risk of autism. In the figure below, we show a DLM for the zinc distribution in teeth of discordant ASD twins. Between 10 weeks before birth and 4 weeks after birth, we saw that ASD affected twins had lower levels of zinc in their teeth.

Overall, by combining recently developed laboratory technology with novel statistical methods, we have been able to measure environmental exposures at over 100 time-points for over a dozen elements simultaneously from a single tissue section.

Advanced data mining approaches in the assessment of urinary concentrations of bisphenols, chlorophenols, parabens and benzophenones in Brazilian children and their association to DNA damage

Human exposure to endocrine disrupting chemicals (EDCs) has received considerable attention over the last three decades. However, little is known about the influence of co-exposure to multiple EDCs on effect-biomarkers such as oxidative stress in Brazilian children. In this study, concentrations of 40 EDCs were determined in urine samples collected from 300 Brazilian children of ages 6–14 years and data were analyzed by advanced data mining techniques. Oxidative DNA damage was evaluated from the urinary concentrations of 8-hydroxy-2′-deoxyguanosine (8OHDG). Fourteen EDCs, including bisphenol A (BPA), methyl paraben (MeP), ethyl paraben (EtP), propyl paraben (PrP), 3,4-dihydroxy benzoic acid (3,4-DHB), methyl-protocatechuic acid (OH-MeP), ethyl-protocatechuic acid (OH-EtP), triclosan (TCS), triclocarban (TCC), 2-hydroxy-4-methoxybenzophenone (BP3), 2,4-dihydroxy-benzophenone (BP1), bisphenol A bis(2,3-dihydroxypropyl) glycidyl ether (BADGE·2H2O), 2,4-dichlorophenol (2,4-DCP), and 2,5-dichlorophenol (2,5-DCP) were found in>50% of the urine samples analyzed. The highest geometric mean concentrations were found for MeP (43.1 ng/mL), PrP (3.12 ng/mL), 3,4- DHB (42.2 ng/mL), TCS (8.26 ng/mL), BP3 (3.71 ng/mL), and BP1 (4.85 ng/mL), and exposures to most of which were associated with personal care product (PCP) use. Statistically significant associations were found between urinary concentrations of 8OHDG and BPA, MeP, 3,4-DHB, OH-MeP, OH-EtP, TCS, BP3, 2,4-DCP, and 2,5-DCP. After clustering the data on the basis of i) 14 EDCs (exposure levels), ii) demography (age, gender and geographic location), and iii) 8OHDG (effect), two distinct clusters of samples were identified. 8OHDG concentration was the most critical parameter that differentiated the two clusters, followed by OH-EtP. When 8OHDG was removed from the dataset, predictability of exposure variables increased in the order of: OHEtP > OH-MeP > 3,4-DHB > BPA > 2,4-DCP > MeP > TCS > EtP > BP1 > 2,5-DCP. Our results showed that co-exposure to OH-EtP, OH-MeP, 3,4-DHB, BPA, 2,4-DCP, MeP, TCS, EtP, BP1, and 2,5-DCP was associated with DNA damage in children. This is the first study to report exposure of Brazilian children to a wide range of EDCs and the data mining approach further strengthened our findings of chemical co-exposures and biomarkers of effect.